Thesis offer Early Detection of Perineal Tissue Damage: An Experimental and Numerical Approach

Updated: about 2 months ago
Location: Ales, LANGUEDOC ROUSSILLON
Job Type: FullTime
Deadline: 31 Aug 2025

3 Mar 2025
Job Information
Organisation/Company

IMT Mines Ales
Department

Human Ressources Department
Research Field

Other
Researcher Profile

First Stage Researcher (R1)
Positions

Master Positions
Country

France
Application Deadline

31 Aug 2025 - 00:00 (UTC)
Type of Contract

Temporary
Job Status

Full-time
Offer Starting Date

1 Apr 2025
Is the job funded through the EU Research Framework Programme?

NextGenerationEU
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

This thesis is part of the European project Pelvitrack (Horizon Europe 2025–2029), which aims to prevent pelvic floor disorders (PFDs). These conditions affect 32% of women1 , primarily due to perineal tears during vaginal deliveries (Figure 1). The project, briefly introduced in a popular science article (The Conversation), adopts an interdisciplinary approach by bringing together experts from various fields, such as thermal engineering, electrical engineering, mechanics, acoustics, optics, computer science, simulation, machine learning, and medical sciences. The goal is to develop a real-time monitoring solution to anticipate and prevent perineal tears during childbirth, thereby minimizing the resulting physical trauma. The consortium, which brings together multidisciplinary expertise, includes European partners such as research institutions like IMT (project lead), Ecole Nationale Supérieure des Mines de Paris, CNRS (LMA in Marseille, LMGC in Montpellier, FEMTO-ST in Besançon), Centrale Lille, the University of Zaragoza (Spain), Politecnico di Torino (Italy), the University of West Bohemia (Czech Republic), INEGI (Portugal), and EPFL (Switzerland). It also involves hospitals like CHU Nîmes, APHM, and CHU Lille, as well as companies such as Superviseme and Virtualcare. The objective is to model the mechanical behavior of perineal tissues with complex microstructures based on laboratory mechanical tests, extract parameters that evolve with microstructure during mechanical stress leading to tissue damage, and establish correlations between these parameters and data from other technologies.

Specific Objectives: 

1. Conduct specific mechanical tests under physiological conditions on perineal tissues from animal perineum samples and complete perineum, simulating the multiaxial stresses experienced during childbirth

2 . These tests will be coupled with optical instrumentation (Image Correlation). Meanwhile, project partners will acquire tissue data during stress using various instruments: Colorimetry, Elastography, Mechanics (suction tests3 , indentation4 ), and Optical Coherence Tomography (OCT). 2. Develop a hyper-viscoelastic model, potentially combined with statistical learning, inspired by existing models5-11. This model will integrate cyclic softening phenomena and predict early signs of perineal tissue damage before rupture. It will incorporate microstructural changes induced by mechanical stress and will be developed based on experimental data from laboratory tests. 

3. Identify relevant mechanical biomarkers, such as anisotropy, viscosity, and relaxation time variations, to detect early damage signs before tissue tears. 4. Correlate mechanical biomarkers with experimental data collected on-site and by project partners using different instruments, to evaluate (ex vivo) the most effective technology for early detection of perineal damage. 

Methodological Approach: 

1. Mechanical Experimentation: Perform multiaxial tests on porcine perineal tissues (biaxial tension, bulge inflation) coupled with macro- and microscopic structural observations to capture local tissue structure evolution under stress. These tests will also assess metrics of selected macro- and meso-scale devices. 

2. Numerical Modeling: Develop a numerical model based on large deformations, including viscoelasticity, damage, and softening mechanisms, followed by the identification and validation of associated biomarkers. 

3. Experimental and Numerical Correlation: Use regression methods and statistical learning to establish robust correlations between macro- and meso-scale data and predicted biomarkers, followed by sensitivity analyses to identify the most effective instrumented solution.

 

Supervision Team: 

IMT Mines Alès has three high-level research and teaching centers focused on materials and civil engineering (C2MA), environment and risks (CREER), and artificial intelligence, industrial, and digital engineering (CERIS). This thesis involves the DMS (Durability of Materials and Structures) team, hosted at LMGC (UMR 5508) and part of C2MA. 

Ecole des Mines de Paris, also known as Mines Paris - PSL, is a prestigious institution recognized for its engineering training and essential research role. It operates 18 laboratories, including the Centre des Matériaux (CDM). This laboratory, affiliated with Mines Paris - PSL and associated with CNRS as UMR 7633 (INSIS Department), conducts internationally renowned scientific research. The CDM's work spans areas such as physical property analysis, mechanical and numerical modeling based on data, and numerical structure simulation. It particularly focuses on the behavior of materials under mechanical and thermal stress. 

This thesis, starting as soon as possible, involves the DMS and CDM teams, with the first year at CDM (including missions to Alès) and the following two years at IMT Mines Alès.


Where to apply
E-mail

anne-sophie.caro@mines-ales.fr

Requirements
Research Field
Other
Education Level
Master Degree or equivalent

Skills/Qualifications

Required Skills: 

• Numerical (finite element) and experimental mechanics. 

• Mechanical modeling of hyperelastic materials. 

• Data analysis and programming (preferably Python).


Internal Application form(s) needed
PELVITRACK_PhD (1).pdf
English
(131.64 KB - PDF)
Download
Additional Information
Selection process

Send your CV, Master 1 and 2 transcript of records, cover letter and at least one recommendation letter, to anne-sophie.caro@mines-ales.fr .


Additional comments

Thesis Director: Anne-Sophie CARO (LMGC/DMS, IMT Mines Alès) 

Co-Director: Sabine CANTOURNET (CDM, Mines Paris - PSL) 

Supervisors: Pierre KERFRIDEN (CDM, Mines Paris - PSL), Sarah IAQUINTA (LMGC/DMS, IMT Mines Alès), André CHRYSOCHOOS (LMGC, University of Montpellier)


Work Location(s)
Number of offers available
1
Company/Institute
IMT Mines Alès
Country
France
Geofield


Contact
State/Province

Occitanie
City

Ales
Website

https://www.imt-mines-ales.fr/
Street

6 avenue de Clavières
Postal Code

30100
E-Mail

aurore.chazel@mines-ales.fr
Phone

0466785062

STATUS: EXPIRED

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